{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 149,
   "id": "93eb9b6b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "开始录音\n",
      "录音结束\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'luyin.wav'"
      ]
     },
     "execution_count": 149,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pyaudio\n",
    "import wave\n",
    "def get_audio(sec):\n",
    "    #创建对象\n",
    "    p = pyaudio.PyAudio()\n",
    "    #创建流：采样位，声道数，缓冲区大小，input = True,framerate:采样频率,nchannels:声道数,nframes:采样点数\n",
    "    stream = p.open(format = pyaudio.paInt16,channels = 2,rate = 16000,input = True,frames_per_buffer = 1024)\n",
    "    #创建式打开音频文件\n",
    "    wf  = wave.open('luyin.wav','wb')\n",
    "    #设置音频文件的属性：声道数，采样位，采样频率\n",
    "    wf.setnchannels(2)\n",
    "    wf.setsampwidth(p.get_sample_size(pyaudio.paInt16))\n",
    "    wf.setframerate(16000)\n",
    "    print('开始录音')\n",
    "    for i in range(int(16000*sec/1024)):\n",
    "        data = stream.read(1024)\n",
    "        wf.writeframes(data)\n",
    "    print('录音结束')\n",
    "    stream.stop_stream()\n",
    "    stream.close()\n",
    "    p.terminate()\n",
    "    wf.close()\n",
    "    return 'luyin.wav'\n",
    "get_audio(6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "id": "114fd82f",
   "metadata": {},
   "outputs": [],
   "source": [
    "#播放音频\n",
    "def play_audio(file):\n",
    "    p = pyaudio.PyAudio()\n",
    "    wf = wave.open(file,'rb')\n",
    "    stream = p.open(format = p.get_format_from_width(wf.getsampwidth()),channels = wf.getnchannels(),rate = wf.getframerate(),output = True)\n",
    "    data = wf.readframes(1024)\n",
    "    while len(data)>0:\n",
    "        stream.write(data)\n",
    "        data = wf.readframes(1024)\n",
    "    stream.stop_stream()\n",
    "    stream.close()\n",
    "    p.terminate()\n",
    "    wf.close()\n",
    "    \n",
    "play_audio('luyin.wav')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "id": "10ca02b8",
   "metadata": {},
   "outputs": [],
   "source": [
    "#读取音频数据\n",
    "f = wave.open('luyin.wav','rb')\n",
    "params = f.getparams()#获取音频数据\n",
    "nchannels, sampwidth, framerate, nframes = params[:4]#将数据赋予变量\n",
    "strData = f.readframes(nframes)#读取音频，字符串格式\n",
    "waveData = np.frombuffer(strData,dtype=np.int16)#将字符串转化为int\n",
    "waveData = waveData * 1.0/(max(abs(waveData)))#wave幅值归一化\n",
    "waveData = np.reshape(waveData,[nframes,nchannels])#将waveData转换为与声道数对应的规格\n",
    "f.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "id": "3fdd2ec1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#画出时域图\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import os\n",
    "time = np.arange(0,nframes) * (1.0 / framerate)#算出音频时间，时间=采样点数/采样率，作为时域图的横坐标\n",
    "fig,ax1 = plt.subplots()\n",
    "ax1.plot(time,waveData[:,0])#取音频数据第一个声道的数据，作出其时域图\n",
    "ax1.set_xlabel(\"Time(s)\")#设置X轴标签\n",
    "ax1.set_ylabel(\"Amplitude\")#设置Y轴标签\n",
    "ax1.set_title(\"left channel wavedata\")#设置图题\n",
    "ax1.grid()#添加网格\n",
    "plt.show()\n",
    "fig,ax2 = plt.subplots()\n",
    "ax2.plot(time,waveData[:,1])#取音频数据中第二个声道的数据，作出其时域图\n",
    "ax2.set_xlabel(\"Time(s)\")\n",
    "ax2.set_ylabel(\"Amplitude\")\n",
    "ax2.set_title(\"right channel wavedata\")\n",
    "ax2.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "id": "679a867c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#高斯噪声\n",
    "gaussian_noise = np.random.normal(0,2,len(waveData[:,0]))#生成高斯噪声（白噪声）数组，长度为原声音信号长度\n",
    "data_noise = waveData[:,0]+0.02 * gaussian_noise#将高斯噪声添加到原音频信号中生成新的音频信号data_noise\n",
    "#画出添加高斯噪声后的音频信号的时域图\n",
    "noiseData1 = data_noise * 1.0/(max(abs(data_noise)))#音频信号幅值归一化\n",
    "time = np.arange(0,nframes) * (1.0 / framerate)#计算音频总时长\n",
    "fig,ax1 = plt.subplots()\n",
    "ax1.plot(time,noiseData1)#画出音频信号时域图\n",
    "ax1.set_xlabel(\"Time(s)\")#设置X轴标签\n",
    "ax1.set_ylabel(\"Amplitude\")#设置Y轴标签\n",
    "ax1.set_title(\"Noised data\")#设置图题\n",
    "ax1.grid()#添加网格\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "id": "e4cf44c7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#布朗噪声\n",
    "brownian_noise = np.cumsum(np.random.uniform(-1,1,len(waveData[:,0])))\n",
    "brownian_noise /= max(abs(brownian_noise)) # 生成布朗噪声\n",
    "data_noise = waveData[:,0]+0.01*brownian_noise#添加噪声\n",
    "noiseData1 = data_noise*1.0/(max(abs(data_noise)))#wave幅值归一化\n",
    "time = np.arange(0,nframes)*(1.0 / framerate)#计算音频总时长\n",
    "plt.plot(time,noiseData1)\n",
    "plt.xlabel(\"Time(s)\")\n",
    "plt.ylabel(\"Amplitude\")\n",
    "plt.title(\"gaussian noise\")\n",
    "plt.grid('on')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "id": "85d840cb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#余弦变换（包）\n",
    "import cv2\n",
    "waveData = cv2.dct(waveData)\n",
    "fig,ax1 = plt.subplots()\n",
    "ax1.plot(time,waveData)\n",
    "ax1.set_xlabel(\"Time(s)\")\n",
    "ax1.set_ylabel(\"Amplitude\")\n",
    "ax1.set_title(\"Single channel wavedata\")\n",
    "ax1.grid('on')#标尺，on：有，off:无。\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "id": "83901b00",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 720x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#信号分帧加窗\n",
    "import numpy as np\n",
    "import wave\n",
    "import matplotlib.pyplot as plt\n",
    "wlen=512\n",
    "inc=128\n",
    "f = wave.open(r\"luyin.wav\", \"rb\")\n",
    "params = f.getparams()#获取数据\n",
    "nchannels, sampwidth, framerate, nframes = params[:4]#将数据赋予变量\n",
    "str_data = f.readframes(nframes)\n",
    "waveData = np.frombuffer(str_data, dtype=np.short)\n",
    "waveData = waveData*1.0/(max(abs(waveData)))\n",
    "time = np.arange(0, wlen) * (1.0 / framerate)\n",
    "signal_length=len(waveData) #信号总长度\n",
    "if signal_length<=wlen: #若信号长度小于一个帧的长度，则帧数定义为1\n",
    "        nf=1\n",
    "else: #否则，计算帧的总长度\n",
    "        nf=int(np.ceil((1.0*signal_length-wlen+inc)/inc))\n",
    "pad_length=int((nf-1)*inc+wlen) #所有帧加起来总的铺平后的长度\n",
    "zeros=np.zeros((pad_length-signal_length,)) #不够的长度使用0填补，类似于FFT中的扩充数组操作\n",
    "pad_signal=np.concatenate((waveData,zeros)) #填补后的信号记为pad_signal\n",
    "indices=np.tile(np.arange(0,wlen),(nf,1))+np.tile(np.arange(0,nf*inc,inc),(wlen,1)).T  #相当于对所有帧的时间点进行抽取，得到nf*nw长度的矩阵\n",
    "indices=np.array(indices,dtype=np.int32) #将indices转化为矩阵\n",
    "frames=pad_signal[indices] #得到帧信号\n",
    "a=frames[30:31]\n",
    "fig,ax1 = plt.subplots()\n",
    "plt.figure(figsize=(10,4))\n",
    "ax1.plot(time,a[0],c=\"g\")\n",
    "ax1.grid()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "id": "89bbd2a0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#加窗\n",
    "def windows(wlen, name='Hamming'):  # 定义窗函数\n",
    "    # Rect/Hanning/Hamming\n",
    "    if name == 'Hamming':  # 汉明窗\n",
    "        window = np.array([0.54 - 0.46 * np.cos(2 * np.pi * n / (wlen - 1)) for n in range(wlen)])\n",
    "    elif name == 'Hanning':  # 海宁窗\n",
    "        window = np.array([0.5 - 0.5 * np.cos(2 * np.pi * n / (wlen - 1)) for n in range(wlen)])\n",
    "    elif name == 'Rect':  # 矩阵窗\n",
    "        window = np.ones(wlen)\n",
    "    return window    \n",
    "b = a[0] * windows(wlen,'Hanning')\n",
    "figure,ax = plt.subplots()\n",
    "ax.plot(time,b)\n",
    "ax1.set_xlabel(\"Time(s)\")#设置X轴标签\n",
    "ax1.set_ylabel(\"Amplitude\")#设置Y轴标签\n",
    "ax.grid()\n",
    "plt.show()\n",
    "b = a[0] * windows(wlen,'Hamming')\n",
    "figure,ax = plt.subplots()\n",
    "ax.plot(time,b)\n",
    "ax.set_xlabel(\"Time(s)\")#设置X轴标签\n",
    "ax.set_ylabel(\"Amplitude\")#设置Y轴标签\n",
    "ax.grid()\n",
    "plt.show()\n",
    "b = a[0] * windows(wlen,'Rect')\n",
    "figure,ax = plt.subplots()\n",
    "ax.plot(time,b)\n",
    "ax.set_xlabel(\"Time(s)\")#设置X轴标签\n",
    "ax.set_ylabel(\"Amplitude\")#设置Y轴标签\n",
    "ax.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "id": "ec3b1344",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 0.9330282   0.86938827  0.7322204   0.59735403  0.46622553  0.33666627\n",
      "  0.25797924  0.18070663  0.16999828  0.16068068  0.17430907  0.18914965\n",
      "  0.19591209  0.20379588  0.19286707  0.18291778  0.15435833  0.12643165\n",
      "  0.0948136   0.06380466  0.03020772 -0.00267276 -0.04062634 -0.07779704\n",
      " -0.10816076 -0.13760012 -0.14732623 -0.15620976 -0.14020866 -0.12355478\n",
      " -0.08736138 -0.05059576 -0.02134382  0.00836956  0.00711903  0.00624108\n",
      " -0.0231728  -0.05228494 -0.08949181 -0.12661841 -0.13966146 -0.15269796\n",
      " -0.12781932 -0.10275166 -0.05466213 -0.00622101  0.03777546  0.08220908\n",
      "  0.09599933  0.11010285]\n"
     ]
    }
   ],
   "source": [
    "#自相关\n",
    "w = 50\n",
    "m = len(waveData)\n",
    "variance = waveData.var()#计算音频数据方差\n",
    "x = waveData-waveData.mean()#计算音频数据与其均值的差值\n",
    "result = np.correlate(x, x, mode = 'full')[-m + 1:-m + w + 1] / (variance * (np.arange(m - 1, m - 1 - w,-1)))\n",
    "print(result)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "id": "7a28cfda",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots()\n",
    "l = np.arange(w)\n",
    "ax.stem(result)#画棒状图\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "id": "23bef1e5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#信号的快速傅里叶变化\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import wave\n",
    "\n",
    "class Wav_FFT(object):\n",
    "    def __init__(self, wav_path=r\"luyin.wav\"):\n",
    "        self.path = wav_path\n",
    "        \n",
    "    def read_wav(self):\n",
    "        with  wave.open(self.path, \"rb\") as f:\n",
    "            parameters = f.getparams()\n",
    "            self.nchannels, self.sampwidth, self.framerate, self.nframes = parameters[:4]            \n",
    "            # 读取波形数据\n",
    "            str_data = f.readframes(self.nframes)\n",
    "            waveData = np.frombuffer(str_data, dtype=np.short)\n",
    "            waveData.shape = -1, self.nchannels\n",
    "            self.waveData = waveData.T\n",
    "            \n",
    "    def FFT(self):\n",
    "        yf = np.fft.fft(self.waveData)# FFT\n",
    "        bias =  (yf[:, 0] / self.nframes).real\n",
    "        yf_amplitude = np.abs(yf)* (2.0/self.nframes)\n",
    "        yf_amplitude[:, 0] = bias #直流分量(0 Hz处)修正\n",
    "        self.yf_amplitude = yf_amplitude[:, 0:self.nframes//2]#有效信息只有一半\n",
    "    \n",
    "    def plot(self):\n",
    "        self.time = np.arange(0, self.nframes) * (1.0 / self.framerate)\n",
    "        self.freq = np.arange(0,self.nframes//2) * self.framerate / self.nframes #实际频率\n",
    "        for i in range(self.nchannels):\n",
    "            plt.subplot(2, self.nchannels, i+1)\n",
    "            axes[0] = plt.plot(self.time, self.waveData[i,:])\n",
    "            axes[0] = plt.xlabel(\"time \")\n",
    "            axes[0] = plt.ylabel(\"signal\")\n",
    "            plt.grid()\n",
    "            axes[0] = plt.title(\"%d Time domain signal\" %(i+1))\n",
    "            plt.subplot(2, self.nchannels, self.nchannels+i+1)\n",
    "            axes[1] = plt.plot(self.freq, self.yf_amplitude[i, :], \"r-\")\n",
    "            axes[1] = plt.xlabel(\"Frequency [Hz]\")\n",
    "            axes[1] = plt.ylabel(\"Amplitude \")\n",
    "            plt.grid()\n",
    "            axes[1] = plt.title(\"FFT (%d Frequency domain signal)\"%(i+1))    \n",
    "        plt.suptitle(\"wav fft\", fontsize =14, color =\"magenta\")\n",
    "        plt.tight_layout()\n",
    "        plt.show()        \n",
    "wav = Wav_FFT(wav_path=r\"luyin.wav\")\n",
    "wav.read_wav()\n",
    "wav.FFT()\n",
    "wav.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "id": "d1a3564d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#卷积\n",
    "import scipy\n",
    "from scipy import signal\n",
    "Gaussian = scipy.signal.gaussian(M=50,std = 20)  # 高斯滤波器\n",
    "# print(gaussian)\n",
    "Gaussian /= np.sum(Gaussian)\n",
    "convolved = np.convolve(b,Gaussian,mode='valid')# 信号与高斯滤波器进行卷积，相当于频域上进行低通滤波\n",
    "fft_convolved = np.fft.rfft(convolved)  # 傅里叶变换转频域\n",
    "freqs2 = np.linspace(0,framerate/2,len(fft_convolved))\n",
    "# 图像显示\n",
    "fig,ax = plt.subplots(figsize=(12,4))\n",
    "ax.plot(freqs2,np.abs(fft_convolved))\n",
    "ax.set_xlabel('frequency(Hz)')\n",
    "ax.set_ylabel('amplitude')\n",
    "ax.set_title('spectrum')\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
